Triple
T14155596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C. W. Post |
E350806
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Postum
Postum is a caffeine-free roasted grain beverage developed in the late 19th century as a coffee substitute and marketed as a healthier alternative.
|
E1083987
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Postum | Statement: [C. W. Post, notableWork, Postum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Postum Context triple: [C. W. Post, notableWork, Postum]
-
A.
Kofy
Kofy is a variant spelling of the given name Kofi, commonly used in some personal or brand contexts.
-
B.
Sanka Coffie
Sanka Coffie is the laid-back, humorous pushcart driver and brakeman who provides comic relief and heart in the Jamaican bobsled team in the film "Cool Runnings."
-
C.
Crema
Crema is a historic town in the Lombardy region of northern Italy, known for its medieval architecture and cultural heritage.
-
D.
The Tea
The Tea is an 1880 oil painting by American Impressionist Mary Cassatt that depicts two women in a refined domestic interior, exemplifying her focus on the private lives of women.
-
E.
Pfeffer
Pfeffer is a German-origin surname borne by various notable individuals across fields such as academia, politics, and the arts.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Postum Triple: [C. W. Post, notableWork, Postum]
Generated description
Postum is a caffeine-free roasted grain beverage developed in the late 19th century as a coffee substitute and marketed as a healthier alternative.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Postum Target entity description: Postum is a caffeine-free roasted grain beverage developed in the late 19th century as a coffee substitute and marketed as a healthier alternative.
-
A.
Kofy
Kofy is a variant spelling of the given name Kofi, commonly used in some personal or brand contexts.
-
B.
Sanka Coffie
Sanka Coffie is the laid-back, humorous pushcart driver and brakeman who provides comic relief and heart in the Jamaican bobsled team in the film "Cool Runnings."
-
C.
Crema
Crema is a historic town in the Lombardy region of northern Italy, known for its medieval architecture and cultural heritage.
-
D.
The Tea
The Tea is an 1880 oil painting by American Impressionist Mary Cassatt that depicts two women in a refined domestic interior, exemplifying her focus on the private lives of women.
-
E.
Pfeffer
Pfeffer is a German-origin surname borne by various notable individuals across fields such as academia, politics, and the arts.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6135744c81909a43d659f5fe2895 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ec6448819087e50aac964ec637 |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd06d23af481909924b61260788f0b |
completed | May 7, 2026, 9:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd075f7a40819097de4bdbd3fad547 |
completed | May 7, 2026, 9:42 p.m. |
Created at: April 10, 2026, 12:58 a.m.